1. Field of the Invention
The invention generally relates to the field of geographic change detection and feature extraction, and to a method for using collections of radio signal beacons to define and monitor the shape and extent of human development and cultural activity.
2. Description of Related Art
Boundaries that accurately describe the extent and density of human presence are an important component of the functional processes of many organizations. These include civil and military governmental units as well as non-governmental entities, commercial organizations and individuals. Accurate land use and cultural characterizations are vital for urban planning, public safety and asset management. These boundaries are generally maintained and implemented using geographic information systems and provide analytical geometry for resource deployment and logistics optimization.
While various sources of and processes for determining the extent and density of the built environment are currently in use, these are either only selectively available or prohibitively expensive to acquire and maintain to desired levels of accuracy. Comprehensiveness and consistency are especially problematic across political borders, and few methods exist for capturing change simultaneously with global extent.
One technique to acquire these data is through population density models. Weaknesses of population density models are that they are usually census-sourced or coarsely sampled, they are generally allocated from larger to smaller areas based on official national or regional counts, and they are maintained to high accuracy in only a very small subset of overall developed areas.
Another source of these data is the acquisition of remotely sensed, spectrally extracted features. Weaknesses of this approach are that it is non-uniform and incomplete at global scales, it must be acquired by specific satellite mission (e.g., Landsat, SPOT, IKONOS, MODIS, Quickbird, WorldView, GeoEye) and post-processed for feature extraction, and its sampling is non-simultaneous.
Another source of these data is satellite-acquired, night-time light propagation. Weaknesses of this approach are that it is low resolution, excludes naturally illuminated (daylit) areas, and variable density within nighttime lighted areas is difficult or impossible to numerically quantify.
Another technique to acquire these data is feature-based density modeling (e.g., roads, buildings, business and residential address locations). Weaknesses of this approach are that is it non-uniform, selectively available, and expensive to acquire and maintain.
Another source of these data is geocoded utility and network traffic archives. The weakness of this source is that it is selectively available, proprietary, and fragmented.
While the existing models and techniques described above may offer useful information regarding the density of human presence and other geographic features, each also suffers from one or more shortcomings. A superior human extent and density metric may couple the accuracy of spectrally extracted aerial imagery polygons with the immediacy of night time light propagation data, and include quantitative density metrics based on population modeling.